Interstitial Cystitis-Associated Urinary Metabolites Identified by Mass-Spectrometry Based Metabolomics Analysis

Tobias Kind, Eunho Cho, Taeeun D. Park, Nan Deng, Zhenqiu Liu, Tack Lee, Oliver Fiehn, Jayoung Kim

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

This study on interstitial cystitis (IC) aims to identify a unique urine metabolomic profile associated with IC, which can be defined as an unpleasant sensation including pain and discomfort related to the urinary bladder, without infection or other identifiable causes. Although the burden of IC on the American public is immense in both human and financial terms, there is no clear diagnostic test for IC, but rather it is a disease of exclusion. Very little is known about the clinically useful urinary biomarkers of IC, which are desperately needed. Untargeted comprehensive metabolomic profiling was performed using gas-chromatography/mass-spectrometry to compare urine specimens of IC patients or health donors. The study profiled 200 known and 290 unknown metabolites. The majority of the thirty significantly changed metabolites before false discovery rate correction were unknown compounds. Partial least square discriminant analysis clearly separated IC patients from controls. The high number of unknown compounds hinders useful biological interpretation of such predictive models. Given that urine analyses have great potential to be adapted in clinical practice, research has to be focused on the identification of unknown compounds to uncover important clues about underlying disease mechanisms.

Original languageEnglish (US)
Article number39227
JournalScientific reports
Volume6
DOIs
StatePublished - Dec 15 2016

Fingerprint

Interstitial Cystitis
Metabolomics
Mass Spectrometry
Urine
Discriminant Analysis
Least-Squares Analysis
Routine Diagnostic Tests
Gas Chromatography-Mass Spectrometry
Urinary Bladder
Biomarkers
Tissue Donors
Pain
Health
Infection
Research

All Science Journal Classification (ASJC) codes

  • General

Cite this

Kind, Tobias ; Cho, Eunho ; Park, Taeeun D. ; Deng, Nan ; Liu, Zhenqiu ; Lee, Tack ; Fiehn, Oliver ; Kim, Jayoung. / Interstitial Cystitis-Associated Urinary Metabolites Identified by Mass-Spectrometry Based Metabolomics Analysis. In: Scientific reports. 2016 ; Vol. 6.
@article{cce5a64d82bc41cf854eac370e0d0a7f,
title = "Interstitial Cystitis-Associated Urinary Metabolites Identified by Mass-Spectrometry Based Metabolomics Analysis",
abstract = "This study on interstitial cystitis (IC) aims to identify a unique urine metabolomic profile associated with IC, which can be defined as an unpleasant sensation including pain and discomfort related to the urinary bladder, without infection or other identifiable causes. Although the burden of IC on the American public is immense in both human and financial terms, there is no clear diagnostic test for IC, but rather it is a disease of exclusion. Very little is known about the clinically useful urinary biomarkers of IC, which are desperately needed. Untargeted comprehensive metabolomic profiling was performed using gas-chromatography/mass-spectrometry to compare urine specimens of IC patients or health donors. The study profiled 200 known and 290 unknown metabolites. The majority of the thirty significantly changed metabolites before false discovery rate correction were unknown compounds. Partial least square discriminant analysis clearly separated IC patients from controls. The high number of unknown compounds hinders useful biological interpretation of such predictive models. Given that urine analyses have great potential to be adapted in clinical practice, research has to be focused on the identification of unknown compounds to uncover important clues about underlying disease mechanisms.",
author = "Tobias Kind and Eunho Cho and Park, {Taeeun D.} and Nan Deng and Zhenqiu Liu and Tack Lee and Oliver Fiehn and Jayoung Kim",
year = "2016",
month = "12",
day = "15",
doi = "10.1038/srep39227",
language = "English (US)",
volume = "6",
journal = "Scientific Reports",
issn = "2045-2322",
publisher = "Nature Publishing Group",

}

Interstitial Cystitis-Associated Urinary Metabolites Identified by Mass-Spectrometry Based Metabolomics Analysis. / Kind, Tobias; Cho, Eunho; Park, Taeeun D.; Deng, Nan; Liu, Zhenqiu; Lee, Tack; Fiehn, Oliver; Kim, Jayoung.

In: Scientific reports, Vol. 6, 39227, 15.12.2016.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Interstitial Cystitis-Associated Urinary Metabolites Identified by Mass-Spectrometry Based Metabolomics Analysis

AU - Kind, Tobias

AU - Cho, Eunho

AU - Park, Taeeun D.

AU - Deng, Nan

AU - Liu, Zhenqiu

AU - Lee, Tack

AU - Fiehn, Oliver

AU - Kim, Jayoung

PY - 2016/12/15

Y1 - 2016/12/15

N2 - This study on interstitial cystitis (IC) aims to identify a unique urine metabolomic profile associated with IC, which can be defined as an unpleasant sensation including pain and discomfort related to the urinary bladder, without infection or other identifiable causes. Although the burden of IC on the American public is immense in both human and financial terms, there is no clear diagnostic test for IC, but rather it is a disease of exclusion. Very little is known about the clinically useful urinary biomarkers of IC, which are desperately needed. Untargeted comprehensive metabolomic profiling was performed using gas-chromatography/mass-spectrometry to compare urine specimens of IC patients or health donors. The study profiled 200 known and 290 unknown metabolites. The majority of the thirty significantly changed metabolites before false discovery rate correction were unknown compounds. Partial least square discriminant analysis clearly separated IC patients from controls. The high number of unknown compounds hinders useful biological interpretation of such predictive models. Given that urine analyses have great potential to be adapted in clinical practice, research has to be focused on the identification of unknown compounds to uncover important clues about underlying disease mechanisms.

AB - This study on interstitial cystitis (IC) aims to identify a unique urine metabolomic profile associated with IC, which can be defined as an unpleasant sensation including pain and discomfort related to the urinary bladder, without infection or other identifiable causes. Although the burden of IC on the American public is immense in both human and financial terms, there is no clear diagnostic test for IC, but rather it is a disease of exclusion. Very little is known about the clinically useful urinary biomarkers of IC, which are desperately needed. Untargeted comprehensive metabolomic profiling was performed using gas-chromatography/mass-spectrometry to compare urine specimens of IC patients or health donors. The study profiled 200 known and 290 unknown metabolites. The majority of the thirty significantly changed metabolites before false discovery rate correction were unknown compounds. Partial least square discriminant analysis clearly separated IC patients from controls. The high number of unknown compounds hinders useful biological interpretation of such predictive models. Given that urine analyses have great potential to be adapted in clinical practice, research has to be focused on the identification of unknown compounds to uncover important clues about underlying disease mechanisms.

UR - http://www.scopus.com/inward/record.url?scp=85006269747&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85006269747&partnerID=8YFLogxK

U2 - 10.1038/srep39227

DO - 10.1038/srep39227

M3 - Article

C2 - 27976711

AN - SCOPUS:85006269747

VL - 6

JO - Scientific Reports

JF - Scientific Reports

SN - 2045-2322

M1 - 39227

ER -